Search

In the current era of digital surveying and mapping to intelligent surveying and mapping, ubiquitous surveying and mapping has brought many opportunities and challenges to college engineering course teaching. With the development of ubiquitous surveying and mapping, college engineering practice courses urgently need to respond to ubiquitous surveying and mapping. The research aims to integrate the development of ubiquitous surveying and mapping into the teaching of engineering practice courses in colleges, including promoting Android, Brower/Server (B/S), and Client/Server (C/S) to build a platform for practice courses. This also incorporates real development cases in measurement data processing such as gravity field refinement. In this way, the teaching level of engineering practice courses in colleges can be improved, and new ideas can be put forward for cultivating surveying and mapping talents in the new era in colleges. Finally, it can also provide new ideas for the organization of surveying and mapping practice courses under the background of the pandemic.

We report new PKS, SKS, and SKKS splitting measurements for 88 seismic stations in Namibia, Botswana, South Africa, and Mozambique. When combined with measurements from previous studies, the ensemble of measurements shows a fairly uniform NNE to NE (∼41° on average) fast‐polarization direction (ϕ) and delay time (δt) (∼0.7 s on average) across the entire southern African subcontinent. It is difficult to attribute the NNE‐NE ϕ direction to just one source of anisotropy either within the lithospheric or sublithospheric mantle. We instead propose the observed anisotropy pattern could result from a combination of several sources that together give rise to a pervasive NNE‐NE ϕ direction; (a) fossil anisotropy in the lithospheric mantle resulting from the Neoproterozoic collision of the Congo and Kalahari cratons to form the Damara Belt, (b) movement of the African plate over the asthenosphere, and (c) flow in the upper mantle induced by the African Superplume. In addition, a contribution from anisotropy in the lowermost mantle in the vicinity of the African large low shear velocity province cannot be ruled out. Plain Language Summary: Seismic anisotropy, or the directional dependence in seismic wave speed, reveals the ancient to present orientation of deformation of Earth's interior. In this study, shear waves refracted through the outer core and recorded at 88 seismic stations located in Namibia, Botswana, South Africa, and Mozambique were measured to constrain the anisotropic structure of the upper mantle beneath southern Africa. Our results, combined with previous results, show a consistent NNE‐NE fast polarization direction. This direction cannot be easily explained by a single source of anisotropy caused either by past collisions of different geological blocks in southern Africa or the present movement of the African plate. Instead, we propose the pattern may result from a combination of three sources, (a) ancient deformation preserved within the deep continental lithosphere developed when the Congo and Kalahari cratons collided, (b) movement of the African plate over the asthenosphere, and (c) the flow of upwelling rock in the mantle beneath Africa. Key Points: Shear wave splitting measurement across southern Africa shows a fairly uniform NNE to NE fast‐polarization direction (ϕ)The observed ϕ direction cannot be easily attributed to just one source of anisotropy within the lithospheric or sublithospheric mantleThe ϕ pattern may reflect several geodynamic processes [ABSTRACT FROM AUTHOR]

For decades, a full numerical description of the spatio-temporal dynamics of a landslide could be achieved only via physics-based models. The part of the geomorphology community focusing on data-driven model has instead focused on predicting where landslides may occur via susceptibility models. Moreover, they have estimated when landslides may occur via models that belong to the early-warning-system or to the rainfall-threshold themes. In this context, few published research have explored a joint spatio-temporal model structure. Furthermore, the third element completing the hazard definition, i.e., the landslide size, has hardly ever been modeled over space and time. However, the technological advancements of data-driven models have reached a level of maturity that allows to model all three components (Where, When and Size) mentioned above. This work, takes this direction and proposes for the first time a solution to the assessment of landslide hazard in a given area by jointly modeling landslide occurrences and their associated areal density per mapping unit, in space and time. To achieve this ambitious task, we have used a spatio-temporal landslide database generated for the Nepalese region affected by the Gorkha earthquake on the 25th of April 2015. The model relies on a deep-learning architecture trained using an Ensemble Neural Network, where the landslide occurrences and densities are aggregated over a squared mapping unit of 1 x 1 km and classified/regressed against a nested 30 m lattice. At the nested level, we have expressed predisposing and triggering factors. As for the temporal units, we have used an approximately 6-month resolution depending on the mapped inventory dates. The results are promising as our model performs satisfactorily both in the classification (susceptibility) and regression (density prediction) tasks. We believe that the model we propose brings a level of novelty that has the potential to create a rift with respect to the common susceptibility literature, finally proposing an integrated framework for hazard modeling in a data-driven context. To promote reproducibility and repeatability of the analyses in this work, we share data and codes in a github repository accessible from this link. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.earscirev.2010.07.005 Byline: Christoph Hecker, Mark van der Meijde, Freek D. van der Meer Keywords: plagioclase; alkali feldspar; infrared; spectroscopy; remote sensing; thermal infrared Abstract: Minerals of the feldspar group are the most common on earth. Feldspars are economically important in two ways: either as industrial minerals or as a vector-to-ore for mineral deposits. In order to use feldspars for classifying rock compositions or metasomatic conditions during rock alteration events, there is a need for analytical methods to identify and classify feldspars. Traditionally, feldspar composition and structure have been investigated using methods such as optical microscopy, electron microprobe analysis (EMPA), cathodoluminescence and X-ray diffraction (XRD) analysis. In this paper infrared techniques (0.7-25[mu]m)) are reviewed in detail and investigated in how far some of the traditional analytical methods can be replaced by infrared spectroscopy. Successes as well as limitations of infrared approaches are highlighted and existing work is scrutinized in terms of its applicability to remote sensing techniques. Even though numerous studies on mid-infrared (MIR) spectroscopy of feldspars exist, their results often cannot be directly related to remote sensing applications. Examples are the effects of feldspar twinning, exsolution textures and structural state on infrared spectra. The applicability of the results to emission remote sensing requires further research. It has been shown that linear unmixing of laboratory infrared spectra of rocks works fairly well. Detection limits for feldspar are around 5% and plagioclase composition can be determined within error margins of [+ or -]4% anorthite component. Infrared spectroscopy can, however, not detect compositional zonation or different generations of feldspars. Infrared spectra represent the current average plagioclase and average alkali feldspar composition in the sample. With several new airborne instruments under development, it is opportune to focus upcoming research efforts on developing standardized processing techniques and spectral feldspar indices for thermal infrared imagery. Commercially interesting products include numbers of feldspars species, plagioclase and alkali feldspar composition, their structural state and relative or semi-quantitative abundance in the rocks. Article History: Received 27 November 2009; Accepted 12 July 2010

Spectral matching algorithms, such as the Spectral Angle Mapper (SAM), utilize the spectral similarity between individual image pixel spectra and a spectral reference library with known components. Here, we illustrate and quantify the effects that different sources of reference libraries have on SAM classification results. Synthetic images of three mineral endmembers were classified by using reference libraries derived from airborne hyperspectral imagery, ground spectra (Portable Infrared Mineral Analyser), and from a standard library (United States Geologic Survey). Results show that the source of the reference library strongly influences the classification results if all available wavelengths are used. This effect can be partially neutralized by using appropriate preprocessing methods. Two different types of spectral subsetting of the data, two types of continuum removal, and a combination thereof were tested. Best results were achieved by using a feature subset (i.e., limiting the input wavelengths to the diagnostic absorption features). This increased the average classification accuracy from 74% to 95% (ground spectral library) and from 68% to 94% (standard library). Index Terms--Image classification, infrared spectroscopy, spectral analysis, Spectral Angle Mapper (SAM), spectral library, spectral similarity measure.